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2020 – today
- 2023
[j3]Anton Tsitsulin, John Palowitch, Bryan Perozzi, Emmanuel Müller:
Graph Clustering with Graph Neural Networks. J. Mach. Learn. Res. 24: 127:1-127:21 (2023)- [j2]Judith Hermanns
, Konstantinos Skitsas, Anton Tsitsulin, Marina Munkhoeva, Alexander Frederiksen Kyster, Simon Nielsen, Alexander M. Bronstein, Davide Mottin, Panagiotis Karras:
GRASP: Scalable Graph Alignment by Spectral Corresponding Functions. ACM Trans. Knowl. Discov. Data 17(4): 50:1-50:26 (2023) - [c11]Brandon A. Mayer, Anton Tsitsulin, Hendrik Fichtenberger, Jonathan Halcrow, Bryan Perozzi:
HUGE: Huge Unsupervised Graph Embeddings with TPUs. KDD 2023: 4638-4648 - [c10]Bryan Perozzi, Sami Abu-El-Haija, Anton Tsitsulin:
Graph Neural Networks in TensorFlow. KDD 2023: 5786-5787 - [c9]Jiaqi Ma, Jiong Zhu, Yuxiao Dong, Danai Koutra, Jingrui He, Qiaozhu Mei, Anton Tsitsulin, Xingjian Zhang, Marinka Zitnik:
The 3rd Workshop on Graph Learning Benchmarks (GLB 2023). KDD 2023: 5870-5871 - [i20]Anton Tsitsulin, Marina Munkhoeva, Bryan Perozzi:
Unsupervised Embedding Quality Evaluation. CoRR abs/2305.16562 (2023) - [i19]Mustafa Yasir, John Palowitch, Anton Tsitsulin, Long Tran-Thanh, Bryan Perozzi:
Examining the Effects of Degree Distribution and Homophily in Graph Learning Models. CoRR abs/2307.08881 (2023) - [i18]Brandon A. Mayer, Anton Tsitsulin, Hendrik Fichtenberger, Jonathan Halcrow, Bryan Perozzi:
HUGE: Huge Unsupervised Graph Embeddings with TPUs. CoRR abs/2307.14490 (2023) - [i17]Bahare Fatemi, Sami Abu-El-Haija, Anton Tsitsulin, Seyed Mehran Kazemi, Dustin Zelle, Neslihan Bulut, Jonathan Halcrow, Bryan Perozzi:
UGSL: A Unified Framework for Benchmarking Graph Structure Learning. CoRR abs/2308.10737 (2023) - 2022
- [c8]John Palowitch, Anton Tsitsulin, Brandon A. Mayer, Bryan Perozzi:
GraphWorld: Fake Graphs Bring Real Insights for GNNs. KDD 2022: 3691-3701 - [c7]Alessandro Epasto, Vahab Mirrokni, Bryan Perozzi, Anton Tsitsulin, Peilin Zhong:
Differentially Private Graph Learning via Sensitivity-Bounded Personalized PageRank. NeurIPS 2022 - [i16]John Palowitch, Anton Tsitsulin, Brandon A. Mayer, Bryan Perozzi:
GraphWorld: Fake Graphs Bring Real Insights for GNNs. CoRR abs/2203.00112 (2022) - [i15]Anton Tsitsulin, Benedek Rozemberczki, John Palowitch, Bryan Perozzi:
Synthetic Graph Generation to Benchmark Graph Learning. CoRR abs/2204.01376 (2022) - [i14]Seyed Mehran Kazemi, Anton Tsitsulin, Hossein Esfandiari, MohammadHossein Bateni, Deepak Ramachandran, Bryan Perozzi, Vahab S. Mirrokni:
Tackling Provably Hard Representative Selection via Graph Neural Networks. CoRR abs/2205.10403 (2022) - [i13]Oleksandr Ferludin, Arno Eigenwillig, Martin Blais, Dustin Zelle, Jan Pfeifer, Alvaro Sanchez-Gonzalez, Wai Lok Sibon Li, Sami Abu-El-Haija, Peter W. Battaglia, Neslihan Bulut, Jonathan Halcrow, Filipe Miguel Gonçalves de Almeida, Silvio Lattanzi, André Linhares, Brandon A. Mayer, Vahab S. Mirrokni, John Palowitch, Mihir Paradkar, Jennifer She, Anton Tsitsulin, Kevin Villela, Lisa Wang, David Wong, Bryan Perozzi:
TF-GNN: Graph Neural Networks in TensorFlow. CoRR abs/2207.03522 (2022) - [i12]Alessandro Epasto, Vahab Mirrokni, Bryan Perozzi, Anton Tsitsulin, Peilin Zhong:
Differentially Private Graph Learning via Sensitivity-Bounded Personalized PageRank. CoRR abs/2207.06944 (2022) - [i11]Kimon Fountoulakis, Dake He, Silvio Lattanzi, Bryan Perozzi, Anton Tsitsulin, Shenghao Yang:
On Classification Thresholds for Graph Attention with Edge Features. CoRR abs/2210.10014 (2022) - [i10]Anton Tsitsulin, Davide Mottin, Panagiotis Karras, Alexander M. Bronstein, Emmanuel Müller:
Spectral Graph Complexity. CoRR abs/2211.01434 (2022) - 2021
- [b1]Anton Tsitsulin:
Similarities and Representations of Graph Structures. University of Bonn, Germany, 2021 - [j1]Anton Tsitsulin, Marina Munkhoeva, Davide Mottin, Panagiotis Karras, Ivan V. Oseledets, Emmanuel Müller:
FREDE: Anytime Graph Embeddings. Proc. VLDB Endow. 14(6): 1102-1110 (2021) - [c6]Judith Hermanns, Anton Tsitsulin, Marina Munkhoeva, Alexander M. Bronstein, Davide Mottin, Panagiotis Karras:
GRASP: Graph Alignment Through Spectral Signatures. APWeb/WAIM (1) 2021: 44-52 - [i9]Judith Hermanns, Anton Tsitsulin, Marina Munkhoeva, Alex M. Bronstein, Davide Mottin, Panagiotis Karras:
GRASP: Graph Alignment through Spectral Signatures. CoRR abs/2106.05729 (2021) - 2020
- [c5]Anton Tsitsulin, Marina Munkhoeva, Davide Mottin, Panagiotis Karras, Alexander M. Bronstein, Ivan V. Oseledets, Emmanuel Müller:
The Shape of Data: Intrinsic Distance for Data Distributions. ICLR 2020 - [c4]Anton Tsitsulin, Marina Munkhoeva, Bryan Perozzi:
Just SLaQ When You Approximate: Accurate Spectral Distances for Web-Scale Graphs. WWW 2020: 2697-2703 - [i8]Anton Tsitsulin, Marina Munkhoeva, Bryan Perozzi:
Just SLaQ When You Approximate: Accurate Spectral Distances for Web-Scale Graphs. CoRR abs/2003.01282 (2020) - [i7]Anton Tsitsulin, Marina Munkhoeva, Davide Mottin, Panagiotis Karras, Ivan V. Oseledets, Emmanuel Müller:
FREDE: Linear-Space Anytime Graph Embeddings. CoRR abs/2006.04746 (2020) - [i6]Anton Tsitsulin, John Palowitch, Bryan Perozzi, Emmanuel Müller:
Graph Clustering with Graph Neural Networks. CoRR abs/2006.16904 (2020) - [i5]Stefan Postavaru, Anton Tsitsulin, Filipe Miguel Gonçalves de Almeida, Yingtao Tian, Silvio Lattanzi, Bryan Perozzi:
InstantEmbedding: Efficient Local Node Representations. CoRR abs/2010.06992 (2020)
2010 – 2019
- 2019
- [c3]Anton Tsitsulin, Davide Mottin, Panagiotis Karras, Alexander M. Bronstein, Emmanuel Müller:
Spectral Graph Complexity. WWW (Companion Volume) 2019: 308-309 - [i4]Anton Tsitsulin, Marina Munkhoeva, Davide Mottin, Panagiotis Karras, Alexander M. Bronstein, Ivan V. Oseledets, Emmanuel Müller:
Intrinsic Multi-scale Evaluation of Generative Models. CoRR abs/1905.11141 (2019) - 2018
- [c2]Anton Tsitsulin, Davide Mottin, Panagiotis Karras, Alexander M. Bronstein, Emmanuel Müller:
NetLSD: Hearing the Shape of a Graph. KDD 2018: 2347-2356 - [c1]Anton Tsitsulin, Davide Mottin, Panagiotis Karras, Emmanuel Müller:
VERSE: Versatile Graph Embeddings from Similarity Measures. WWW 2018: 539-548 - [i3]Anton Tsitsulin, Davide Mottin, Panagiotis Karras, Emmanuel Müller:
VERSE: Versatile Graph Embeddings from Similarity Measures. CoRR abs/1803.04742 (2018) - [i2]Anton Tsitsulin, Davide Mottin, Panagiotis Karras, Alexander M. Bronstein, Emmanuel Müller:
NetLSD: Hearing the Shape of a Graph. CoRR abs/1805.10712 (2018) - [i1]Anton Tsitsulin, Davide Mottin, Panagiotis Karras, Alexander M. Bronstein, Emmanuel Müller:
SGR: Self-Supervised Spectral Graph Representation Learning. CoRR abs/1811.06237 (2018)
Coauthor Index
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last updated on 2023-09-28 03:31 CEST by the dblp team
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